Accurate identification of pathogenic species is important for early appropriate patient management, but growing diversity of infectious species/strains makes the identification of clinical yeasts increasingly difficult. Among conventional methods that are commercially available, the API ID32C, AuxaColor, and Vitek 2 systems are currently the most used systems in routine clinical microbiology. We performed a systematic review and meta-analysis to estimate and to compare the accuracy of the three systems, in order to assess whether they are still of value for the species-level identification of medically relevant yeasts. After adopting rigorous selection criteria, we included 26 published studies involving Candida and non-Candida yeasts that were tested with the API ID32C (674 isolates), AuxaColor (1,740 isolates), and Vitek 2 (2,853 isolates) systems. The random-effects pooled identification ratios at the species level were 0.89 (95% confidence interval [CI], 0.80 to 0.95) for the API ID32C system, 0.89 (95% CI, 0.83 to 0.93) for the AuxaColor system, and 0.93 (95% CI, 0.89 to 0.96) for the Vitek 2 system (P for heterogeneity, 0.255). Overall, the accuracy of studies using phenotypic analysis-based comparison methods was comparable to that of studies using molecular analysis-based comparison methods. Subanalysis of studies conducted on Candida yeasts showed that the Vitek 2 system was significantly more accurate (pooled ratio, 0.94 [95% CI, 0.85 to 0.99]) than the API ID32C system (pooled ratio, 0.84 [95% CI, 0.61 to 0.99]) and the AuxaColor system (pooled ratio, 0.76 [95% CI, 0.67 to 0.84]) with respect to uncommon species (P for heterogeneity, <0.05). Subanalysis of studies conducted on non-Candida yeasts (i.e., Cryptococcus, Rhodotorula, Saccharomyces, and Trichosporon) revealed pooled identification accuracies of ≥98% for the Vitek 2, API ID32C (excluding Cryptococcus), and AuxaColor (only Rhodotorula) systems, with significant low or null levels of heterogeneity (P > 0.05). Nonetheless, clinical microbiologists should reconsider the usefulness of these systems, particularly in light of new diagnostic tools such as matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry, which allow for considerably shortened turnaround times and/or avoid the requirement for additional tests for species identity confirmation.

Accurate identification of pathogenic species is important for early appropriate patient management, but growing diversity of infectious species/strains makes the identification of clinical yeasts increasingly difficult. Among conventional methods that are commercially available, the API ID32C, AuxaColor, and Vitek 2 systems are currently the most used systems in routine clinical microbiology. We performed a systematic review and meta-analysis to estimate and to compare the accuracy of the three systems, in order to assess whether they are still of value for the species-level identification of medically relevant yeasts. After adopting rigorous selection criteria, we included 26 published studies involving Candida and non-Candida yeasts that were tested with the API ID32C (674 isolates), AuxaColor (1,740 isolates), and Vitek 2 (2,853 isolates) systems. The random-effects pooled identification ratios at the species level were 0.89 (95% confidence interval [CI], 0.80 to 0.95) for the API ID32C system, 0.89 (95% CI, 0.83 to 0.93) for the AuxaColor system, and 0.93 (95% CI, 0.89 to 0.96) for the Vitek 2 system (P for heterogeneity, 0.255). Overall, the accuracy of studies using phenotypic analysis-based comparison methods was comparable to that of studies using molecular analysis-based comparison methods. Subanalysis of studies conducted on Candida yeasts showed that the Vitek 2 system was significantly more accurate (pooled ratio, 0.94 [95% CI, 0.85 to 0.99]) than the API ID32C system (pooled ratio, 0.84 [95% CI, 0.61 to 0.99]) and the AuxaColor system (pooled ratio, 0.76 [95% CI, 0.67 to 0.84]) with respect to uncommon species (P for heterogeneity, <0.05). Subanalysis of studies conducted on non-Candida yeasts (i.e., Cryptococcus, Rhodotorula, Saccharomyces, and Trichosporon) revealed pooled identification accuracies of ≥98% for the Vitek 2, API ID32C (excluding Cryptococcus), and AuxaColor (only Rhodotorula) systems, with significant low or null levels of heterogeneity (P > 0.05). Nonetheless, clinical microbiologists should reconsider the usefulness of these systems, particularly in light of new diagnostic tools such as matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry, which allow for considerably shortened turnaround times and/or avoid the requirement for additional tests for species identity confirmation.